Ministry of Agriculture

About: Ministry of Agriculture is a government organization based out in Rio de Janeiro, Brazil. It is known for research contribution in the topics: Chemistry & Salmonella. The organization has 1153 authors who have published 1189 publications receiving 14442 citations.

Seroprevalence, spatial analysis and risk factors of infection with Neospora caninum in cattle in Brazil's northern Pantanal wetland.

Abstract: Neosporosis is caused by an obligate intracellular protozoan, Neospora caninum . It is considered one of the most widespread and frequent causes of abortion in cattle worldwide. To evaluate the prevalence of anti-N. caninum antibodies and associated risk factors, serum samples were collected from 2,452 bovines at 262 farms in the northern Pantanal, state of Mato Grosso, Brazil. Each farmer was asked to fill out a questionnaire for subsequent epidemiological data analysis. Anti-N. caninum antibodies were detected by means of the indirect immunofluorescent assay (IFA), using a cut-off dilution of 1:100. The overall anti-N. caninum antibodies prevalence was 25.44% (Confidence Interval - CI 95%; 20.10%; 30.78%), and the anti-N. caninum antibodies prevalence per herd was 76.72% (CI 95%; 71.60%; 81.84%). The presence of dogs, occurrence of abortion in cows, and sale of cattle for breeding were statistically associated with seropositivity in herds, while the risk of females being seropositive for N. caninum was higher in animals ≤ 6-years-old and in the presence of dogs. A spatial analysis indicated that the relative risk of the disease is spatially constant and that the farms with the highest prevalence of anti-N. caninum antibodies are located south of the region under study.

Object-based land use and land cover mapping from LiDAR data and orthophoto application of decision tree-based data selection for SVM classification

Abstract: The major disadvantage of Support Vector Machine (SVM) happens in its training phase as it requires to solve a quadratic programming problem, making computation very costly. With the integration of LiDAR data and high spatial resolution orthophoto, more input data layers are available for object-based Support Vector Machine classification. Initially, confusion among classes arises because of the presence of irrelevant and redundant data layers. Hence, this study applies Decision Tree (DT), a popular data mining technique, as a pre-classification process in SVM to select the relevant features from the input variables. We assessed the effectiveness of seven vegetation indices, two vegetation index combinations and 14 LiDAR height metrics for mapping agricultural resources in Calatagan, Batangas. We were able to filter the input variables and subsequently achieve at least 73% reduction of training features. With the DT-based feature selection, we were able to reduce the number of input features as well as make the SVM training and classification time shorter by more than 90%. Importantly, the overall accuracy and kappa index of agreement both increased when DT-based SVM was used in contrast with using all the variables for SVM classification.

Reports of Brazilian federal meat inspection system in swine slaughterhouses

Abstract: In the last decades the pig production improvement had impacted on zoonotic profile attributed to pork. This fact has created a need to modernize the meat inspection system traditionally applied, driving the focus to risks that really threaten food safety nowadays. This modernization is a trend in meat producer countries and European Union is ahead in this process. In this way, Brazil is assessing the new systems and building an own proposal which has been conducted under a national project linked by many coordinated actions. The first step of this work is to analyze the data of current inspection system. Then, the aim of this study is to evaluate the carcasses and viscera disposition reported by Brazilian Federal Meat Inspection. The analyzed database encompasses the reports of 114 slaughterhouses recorded from 2012 to 2014 into SIGSIF platform. The results were summarized by descriptive statistics on tables and figures using the SAS software. It was possible to show that the major “post mortem” causes of carcass/viscera trimming or condemnation were resulted from production diseases, as adherences (3.72%), pleurisy (0.85%), abscess (0.58%) and pneumonia (0.20%). Likewise for industrial process problems, as carcass contamination by evisceration leaking (1.8%) and traumatic lesions (1.57%). Zoonosis injuries condemnations were reported in very low frequency in a few slaughterhouses, usually once. Among the total of organs and carcass inspected, cysticercosis was registered in just 0.00092% in 25 slaughterhouses, endocarditis in 0.00193% (23 slaughterhouses), erysipelas in 0.0045% (38 slaughterhouses), sarcosporidiosis in 0.00051% (17 slaughterhouses) and tuberculosis in 0.000046% (12 slaughterhouses). Thus, the current meat inspection system is prepared to detect zoonosis that no longer occur or happen in very low frequency. In the other hand, the traditional ante and post mortem inspection methodologies are not able to detect the main current foodborne pathogens globally distributed as Salmonella.